Labelbox
Free tierThe data factory for AI teams — powering the world's most ambitious AI labs
Key strengths
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Labelbox — Documentation & Integration Guide
API & Connectivity
Labelbox exposes a full API, enabling developers to programmatically trigger agents, configure workflows, manage sessions, and retrieve graded performance data. Agents can also be invoked via external events — including scheduled jobs, incoming alerts, repository commits, and direct API calls — making it straightforward to embed Labelbox into existing CI/CD pipelines and MLOps infrastructure.
Model Provider Configuration
Labelbox supports multiple AI model backends. Teams can configure agents to run on Claude, GPT, Gemini, or open-weights models, allowing flexibility to match model choice to task requirements, cost targets, or compliance constraints.
Integration Ecosystem
Labelbox connects natively with 24+ tools across key categories:
| Category | Integrations |
|---|---|
| Dev & Engineering | GitHub, Jenkins, Vercel, Sentry |
| Data & ML | BigQuery, Databricks, Snowflake, Looker, Google Cloud, Google Cloud Logging |
| Collaboration | Slack, Jira, Linear, Confluence, Notion, Google Drive, Google Calendar |
| Security & Ops | Okta, PagerDuty, Datadog |
| Business Systems | Salesforce, Gong, DocuSign, Amplitude |
Agent Memory & Grading
Each agent session is graded, and results feed into a persistent memory layer that accumulates skills over time. This architecture supports continuous improvement loops without requiring manual retraining cycles.